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You searched for +publisher:"McMaster University" +contributor:("Terlaky, Tamas"). Showing records 1 – 2 of 2 total matches.

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McMaster University

1. Romanko, Oleksandr. Parametric and Multiobjective Optimization with Applications in Finance.

Degree: PhD, 2010, McMaster University

In this thesis parametric analysis for conic quadratic optimization problems is studied. In parametric analysis, which is often referred to as parametric optimization or parametric programming, a perturbation parameter is introduced into the optimization problem, which means that the coefficients in the objective function of the problem and in the right-hand-side of the constraints are perturbed. First, we describe linear, convex quadratic and second order cone optimization problems and their parametric versions. Second, the theory for finding solutions of the parametric problems is developed. We also present algorithms for solving such problems. Third, we demonstrate how to use parametric optimization techniques to solve multiobjective optimization problems and compute Pareto efficient surfaces. We implement our novel algorithm for hi-parametric quadratic optimization. It utilizes existing solvers to solve auxiliary problems. We present numerical results produced by our parametric optimization package on a number of practical financial and non-financial computational problems. In the latter we consider problems of drug design and beam intensity optimization for radiation therapy. In the financial applications part, two risk management optimization models are developed or extended. These two models are a portfolio replication framework and a credit risk optimization framework. We describe applications of multiobjective optimization to existing financial models and novel models that we have developed. We solve a number of examples of financial multiobjective optimization problems using our parametric optimization algorithms.

Thesis

Doctor of Philosophy (PhD)

Advisors/Committee Members: Terlaky, Tamas, Deza, Antoine, Computing and Software.

Subjects/Keywords: Parametric; Multiobjective Optimization; Finance; conic quadratic

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Romanko, O. (2010). Parametric and Multiobjective Optimization with Applications in Finance. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/19370

Chicago Manual of Style (16th Edition):

Romanko, Oleksandr. “Parametric and Multiobjective Optimization with Applications in Finance.” 2010. Doctoral Dissertation, McMaster University. Accessed October 14, 2019. http://hdl.handle.net/11375/19370.

MLA Handbook (7th Edition):

Romanko, Oleksandr. “Parametric and Multiobjective Optimization with Applications in Finance.” 2010. Web. 14 Oct 2019.

Vancouver:

Romanko O. Parametric and Multiobjective Optimization with Applications in Finance. [Internet] [Doctoral dissertation]. McMaster University; 2010. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/11375/19370.

Council of Science Editors:

Romanko O. Parametric and Multiobjective Optimization with Applications in Finance. [Doctoral Dissertation]. McMaster University; 2010. Available from: http://hdl.handle.net/11375/19370


McMaster University

2. Peshko, Olesya. Design of a System for Target Localization and Tracking in Image-Guided Radiation Therapy.

Degree: PhD, 2016, McMaster University

This thesis contributes to the topic of image-based feature localization and tracking in fluoroscopic (2D x-ray) image sequences. Such tracking is needed to automatically measure organ motion in cancer patients treated with radiation therapy. While the use of 3D cone-beam computed tomography (CBCT) images is a standard clinical practice for verifying the agreement of the patient's position to a plan, it is done before the treatment procedure. Hence, measurement of the motion during the procedure could improve plan design and the accuracy of treatment delivery. Using an existing CBCT imaging system is one way of collecting fluoroscopic sequences for such analysis. Since x-ray images of soft tissues are typically characterized with low contrast and high noise, radio-opaque fiducial markers are often inserted in or around the target. This thesis describes techniques that comprise a complete system for automated detection and tracking of the markers in fluoroscopic image sequences. One of the cornerstone design ideas in this thesis is the use of the 3D CBCT image of the patient, from which the markers can be extracted more easily, to initialize the tracking in the fluoroscopic image sequences. To do this, a specific marker-based image registration framework was proposed. It includes multiple novel techniques, such as marker segmentation and modelling, the marker enhancement filter, and marker-specific template image generation approaches. Through extensive experiments on testing data sets, these novel techniques were combined with appropriate state-of-the-art methods to produce a sleek, computationally efficient, fully automated system that achieved reliable marker localization and tracking. The accuracy of the system is sufficient for clinical implementation. The thesis demonstrates an application of the system to the images of prostate cancer patients, and includes examples of statistical analysis of organ motion that can be used to improve treatment planning.

Dissertation

Doctor of Philosophy (PhD)

This thesis presents the development of a software system that analyzes sequences of 2D x-ray images to automatically measure organ motion in patients undergoing radiation therapy for cancer treatment. The knowledge of motion statistics obtained from this system creates opportunities for patient-specific treatment design that may lead to a better outcome. Automated processing of organ motion is challenging due to the low contrast and high noise levels in the x-ray images. To achieve reliable detection, the proposed system was designed to make use of 3D cone-beam computed tomography images of the patient, where the features (markers) are easier to identify. This required the development of a specific image registration framework for aligning the images, including a number of novel feature modelling and image processing techniques. The proposed motion tracking approach was implemented as a complete software system that was extensively validated on phantom and patient studies. It achieved a level of…

Advisors/Committee Members: Davidson, Timothy N., Modersitzki, Jan, Moseley, Douglas J., Terlaky, Tamas, Computational Engineering and Science.

Subjects/Keywords: feature detection; motion tracking; digital filtering; fiducial markers; image registration; radiation therapy

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Peshko, O. (2016). Design of a System for Target Localization and Tracking in Image-Guided Radiation Therapy. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/19136

Chicago Manual of Style (16th Edition):

Peshko, Olesya. “Design of a System for Target Localization and Tracking in Image-Guided Radiation Therapy.” 2016. Doctoral Dissertation, McMaster University. Accessed October 14, 2019. http://hdl.handle.net/11375/19136.

MLA Handbook (7th Edition):

Peshko, Olesya. “Design of a System for Target Localization and Tracking in Image-Guided Radiation Therapy.” 2016. Web. 14 Oct 2019.

Vancouver:

Peshko O. Design of a System for Target Localization and Tracking in Image-Guided Radiation Therapy. [Internet] [Doctoral dissertation]. McMaster University; 2016. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/11375/19136.

Council of Science Editors:

Peshko O. Design of a System for Target Localization and Tracking in Image-Guided Radiation Therapy. [Doctoral Dissertation]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/19136

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